Triple
T24419228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Castroville, California |
E615677
|
entity |
| Predicate | distanceToSalinasInMiles |
P155854
|
FINISHED |
| Object | 15 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 15 | Statement: [Castroville, California, distanceToSalinasInMiles, 15]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToSalinasInMiles Context triple: [Castroville, California, distanceToSalinasInMiles, 15]
-
A.
distanceToSanJosé
Indicates the spatial distance between a given entity and the location of San José.
-
B.
distanceFromSanJosé
Indicates the measured spatial distance between a given entity and the location of San José.
-
C.
distanceToSanDiego
Indicates the measured or estimated distance between a given entity’s location and the city of San Diego.
-
D.
distanceFromMonterey
Indicates the measured distance between a given entity’s location and the location of Monterey.
-
E.
distanceToSanBernardino
Indicates the measured distance between a given entity’s location and the location of San Bernardino.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e2d7e9bfac8190a748952a90957106 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f296a12a50819099fcdbc7096b53dd |
completed | April 29, 2026, 11:39 p.m. |
| PD | Predicate disambiguation | batch_69f287cc4fd4819081e93cc638d9512d |
completed | April 29, 2026, 10:35 p.m. |
| PDg | Predicate description generation | batch_69f2915233c48190a181c8c1924e892c |
completed | April 29, 2026, 11:16 p.m. |
Created at: April 18, 2026, 2:13 a.m.